import numpy


class ChannelSelector(object):
    """Select 1ch from multi-channel signal """

    def __init__(self, train_channel='random', eval_channel=0, axis=1):
        self.train_channel = train_channel
        self.eval_channel = eval_channel
        self.axis = axis

    def __repr__(self):
        return ('{name}(train_channel={train_channel}, '
                'eval_channel={eval_channel}, axis={axis})'
                .format(name=self.__class__.__name__,
                        train_channel=self.train_channel,
                        eval_channel=self.eval_channel,
                        axis=self.axis))

    def __call__(self, x, train=True):
        # Assuming x: [Time, Channel] by default

        if x.ndim <= self.axis:
            # If the dimension is insufficient, then unsqueeze
            # (e.g [Time] -> [Time, 1])
            ind = tuple(slice(None) if i < x.ndim else None
                        for i in range(self.axis + 1))
            x = x[ind]

        if train:
            channel = self.train_channel
        else:
            channel = self.eval_channel

        if channel == 'random':
            ch = numpy.random.randint(0, x.shape[self.axis])
        else:
            ch = channel

        ind = tuple(slice(None) if i != self.axis else ch
                    for i in range(x.ndim))
        return x[ind]
